ARTIFICIAL INTELLIGENCE-LOGIC AND REASONING

CSE3ALR

Not currently offered

Credit points: 15

Subject outline

In this subject, students are provided with the opportunity to study some major research areas of Artificial Intelligence. Topics include PROLOG programming, Logic Programming, Natural Language Processing, Planning and Semantic Web.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorFei Liu

Available to Study Abroad StudentsYes

Subject year levelYear Level 3 - UG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites CSE1IOO

Co-requisitesN/A

Incompatible subjects CSE3AIL

Equivalent subjectsN/A

Special conditionsN/A

Graduate capabilities & intended learning outcomes

01. Apply the knowledge in automated reasoning to analyse and evaluate a reasoning resolution in order to select a proper reasoning resolution to design and implement an intelligent computer system.

Activities:
In lectures, students learn formal language and formal system; understand first order logic as a formal system; and study SLD-resolution (substitution, unification, SLD-derivation, selection rule, ordering rule and computation rule), soundness and completeness. Students learn the contents by listening to the lecture, participating in class discussion, doing the class exercises and completing the lab questions.
Related graduate capabilities and elements:
Creative Problem-solving (Creative Problem-solving)
Inquiry/ Research (Inquiry/ Research)
Critical Thinking (Critical Thinking)

02. Apply the sentence parsing techniques in natural language analysis and evaluation in order to select a parsing technique and implement a computer system to analyse different components of a sentence for the purpose of linguistic analysis and language translation

Activities:
In lectures, students study Specification and Parsing Using Context-Free Grammars and apply it in sentence parsing and decomponent. Students learn the contents by listening to the lecture, participating in class discussion, doing the class exercises and completing the lab questions.
Related graduate capabilities and elements:
Critical Thinking (Critical Thinking)
Creative Problem-solving (Creative Problem-solving)
Inquiry/ Research (Inquiry/ Research)

03. Design, code and evaluate an AI system being implemented in PROLOG.

Activities:
In lectures, students learn PROLOG program design and programming skills such as recursion, iteration, selection, file operations, list operations, structures and pre-defined predicates. Students learn the contents by listening to the lecture, participating in class discussion, doing the class exercises and completing the lab questions. The exam tests this knowledge through short question-answer and PROLOG programming questions.
Related graduate capabilities and elements:
Critical Thinking (Critical Thinking)
Creative Problem-solving (Creative Problem-solving)
Inquiry/ Research (Inquiry/ Research)

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